Spatial transcriptomic analysis of tumor heterogeneity in HPV+ and HPV- Head and Neck Squamous Cell Carcinoma
RNA-seq (gene expression) · human · 39 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- Head and neck cancerThis series is part of our curated briefing on it.
- Samples
- 39 samples: 39 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE268014_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1114040 and SRA study SRP508955. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 39 sample titles: 39 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8283897 P5909, spatial transcriptomics
- GSM8283898 P5903, spatial transcriptomics
- GSM8283899 P5767, spatial transcriptomics
- GSM8283900 P5766, spatial transcriptomics
- GSM8283901 P5764, spatial transcriptomics
- GSM8283902 P5756, spatial transcriptomics
- GSM8283903 P5751, spatial transcriptomics
- GSM8283904 P5736, spatial transcriptomics
- GSM8283905 P5735, spatial transcriptomics
- GSM8283906 P5710, spatial transcriptomics
- GSM8283907 P5709, spatial transcriptomics
- GSM8283908 P5707, spatial transcriptomics
- GSM8283909 P5692, spatial transcriptomics
- GSM8283910 P5684, spatial transcriptomics
- GSM8283911 P5666, spatial transcriptomics
- GSM8283912 P5659, spatial transcriptomics
- GSM8283913 P5636, spatial transcriptomics
- GSM8283914 P5624, spatial transcriptomics
- GSM8283915 P5612, spatial transcriptomics
- GSM8283916 P5469, spatial transcriptomics
- GSM8283917 P5456, replicate 1, spatial transcriptomics
- GSM8283918 P5448, spatial transcriptomics
- GSM8283919 P5418, spatial transcriptomics
- GSM8283920 P5219, spatial transcriptomics
- GSM8283921 P5217, spatial transcriptomics
- GSM8348695 P5457_1, spatial transcriptomics
- GSM8693473 P5666 scRNA-seq library
- GSM8693474 P5684 scRNA-seq library
- GSM8693475 P5710 scRNA-seq library
- GSM8693476 P5735 scRNA-seq library
- GSM8693477 P5736 scRNA-seq library
- GSM8693478 P5751 scRNA-seq library
- GSM8693479 P5418 scRNA-seq library
- GSM8693480 P5448 scRNA-seq library
- GSM8693481 P5469 scRNA-seq library
- GSM8693482 P5219 scRNA-seq library
- GSM8693483 P5217 scRNA-seq library
- GSM9701483 P5684, high resolution spatial transcriptomics
- GSM9701484 P5624, high resolution spatial transcriptomics
- GSE140042 Single-cell atlas of head and neck squamous cell carcinoma 18 samples same disease briefing · shares squamous, head, neck
- GSE185965 Single cell RNA sequencing of head and neck squamous carcinoma (HNSCC) patient sample 3 samples same disease briefing · shares squamous, head, neck
- GSE173647 Single-cell Sequencing Analysis of Head and Neck Squamous Cell Carcinoma 2 samples same disease briefing · shares squamous, head, neck
- GSE182227 Cellular states are coupled to genomic and viral heterogeneity in HPV-related oropharyngeal carcinoma 24 samples same disease briefing · shares hpv, heterogeneity
- GSE164690 Investigating Immune and Non-Immune Cell Interactions in Head and Neck Tumors by Single-Cell RNA Sequencing 51 samples same disease briefing · shares head, neck
- GSE103322 Single cell RNA-seq analysis of head and neck cancer 5901 samples same disease briefing · shares head, neck
- GSE139324 Immune landscape of viral- and carcinogen-drived head and neck cancer 63 samples same disease briefing · shares head, neck
- GSE181919 Single-cell transcriptome profiling of the stepwise progression of head and neck cancer 37 samples same disease briefing · shares head, neck
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.